Advocacy Agent
Find customers whose health score has stayed high for a quarter, identify the kind of advocacy each contact is best placed to offer, and create a task with the specific ask.
- Trigger: a customer’s health score stays high for a quarter
- AI steps: recommend a reference call, case study, or review from what each contact has said publicly
- Output: advocacy tasks assigned to Customer Success and marketing
Agent breakdown
A blueprint to adapt, not a fixed recipe. Set the trigger, thresholds, and methodology that fit your team, and each step builds on the last, using the conversation and CRM context you already capture.
Run on sustained health, not a peak
The agent waits until a customer’s health score has stayed high for a quarter before it runs. This avoids asking after one good month when the account may not be ready to advocate.
- Trigger: A customer’s health score stays high for a quarter
- Condition: Sustained health rather than a one-month peak
Pull the people and their history
Next, the agent pulls the sponsor and champion, along with their sentiment and how long they have been at the customer. It excludes anyone already asked this year and ranks the remaining contacts by sentiment, so the same customer is not asked too often.
- Fields: Sentiment and tenure
- Excludes: Anyone asked already this year
- Ranks: By sentiment
Say what each could give
For each candidate, the agent recommends whether they are best placed to give a reference call, take part in a case study, or leave a review. It bases the recommendation on what the contact has already said publicly rather than on the account’s health score.
For each advocacy candidate, recommend what they are best placed to give: a reference call, a case study, or a review.
Input: each candidate and what they have already said publicly.
- Choose one advocacy ask for each candidate: reference call, case study, or review.
- Explain which public statement supports the recommendation.
- Base the recommendation on what the candidate has said publicly, not on the account’s health score.
Return a list with the candidate, the recommended ask, and the public statement that supports it.
Suggest the specific ask
Once the recommendations are ready, the agent creates a task for Customer Success and marketing that names the specific ask. This gives the owner something concrete to act on before the next review instead of a vague note that the account is happy.
- Due: Before the next review
- Suggests: The specific ask
- Excludes: Anyone in escalation
Advocacy tasks with specific asks assigned to Customer Success and marketing
See which healthy customers are ready for an advocacy ask and whether each contact is best placed for a reference call, a case study, or a review. Each task names the specific ask and is due before the next review, while anyone in escalation or already asked this year is left out.
AI Agents that pair well
Same data, different jobs. Run them together for a fuller picture.
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